Coordinate measuring machines (CMMs) are generally used to inspect an array of features of a part to determine whether each of the features of the part comply with a maximum tolerance for the part; for example, a CMM may be used to inspect an array of pins on a substrate. Generally, the CMM is used to determine the actual positions of the array of pins relative to a set of datum that constrain all six degrees of freedom from motion. In the case of a two-part or composite position tolerance where the lower segment leaves one or more of the degrees of freedom to best benefit the pattern of an array of features, such as an array of pins or pin field, there is an opportunity to select a fitting algorithm, referred to herein as “soft gauging,” that produces results appropriate for the actual requirements of the part.
While soft gauging may include least squares fit and minimum zone algorithms to determine the location of a single prismatic feature (e.g., plain, cylinder, line), there are no minimum zone algorithms readily available for patterns of features, such as an array of pins. According to the American Society of Mechanical Engineers (ASME) Specification Y14.5M-1994 (“Y14.5”), when position tolerance is applied to a pattern of features, all features within the pattern (even the worst feature) must meet that tolerance for the part to be accepted.
Traditionally, compliance of some part to meet a minimum tolerance, such as, for example, an array of features representing, for example, an array of pins on a substrate, is performed using a hard functional gauge. In the past, hard functional gauge could be generated to see whether the given pins on the part could be fit to a corresponding socket. As a result, when using a hard functional gauge for the purpose of evaluating a part for some required positional tolerance, the operator is free to do any manual repositioning, bumping, rotating or moving of the part to determine whether the part may fit into a corresponding socket.
Although Y14.5 only states the definition of the tolerance zone, it does not address what method should be used to demonstrate compliance to the drawing. Readers of an inspection report might want to know how good the part is, not simply whether it passed or failed. When the success criterion is the size of the tolerance zone that is required to contain the worst case point, a minimum zone algorithm will distinguish between a passing part and one that will fail, and additionally provide quantitative information regarding the actual worst case position. When using soft gauging, the algorithms employed are not able to do the same repositioning traditionally performed using hard functional gauges. Failure to do so results in over-rejection of parts that may actually pass, had they been positioned with sufficient accuracy to meet the specification.
Hence, current methods employed in the industry, use a simple translation based on average X, and Y offsets, or use Least Squares algorithms on all, or a portion, of the features in the array to determine a frame of reference. A Least Squares algorithm, seeks to minimize the sum (or average) of the squares of the deviations. This has the effect of favoring the majority of the pins and allowing those that are outliers within the set to have large deviations. Neither of these are optimal solutions, and none of these meet the intent of the ASME Y14.5M-1994 specification for evaluation of true position. Using current algorithms will result in over-rejection of parts, and an inaccurate estimation of process capability for true position.